{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\RR3\Replication Files\JPR-PAM-ID-JOSHI, QUINN & REGAN.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 8 Oct 2014, 10:21:45
{txt}
{com}. 
. 
. //Replicate Table 3
. list year powtran_implem powtran_revers if caseid ==3
{txt}
     {c TLC}{hline 6}{c -}{hline 10}{c -}{hline 10}{c TRC}
     {c |} {res}year   powtra~m   powtra~s {txt}{c |}
     {c LT}{hline 6}{c -}{hline 10}{c -}{hline 10}{c RT}
 21. {c |} {res}1998          2          0 {txt}{c |}
 22. {c |} {res}1999          3          0 {txt}{c |}
 23. {c |} {res}2000          3          0 {txt}{c |}
 24. {c |} {res}2001          3          0 {txt}{c |}
 25. {c |} {res}2002          3          2 {txt}{c |}
     {c LT}{hline 6}{c -}{hline 10}{c -}{hline 10}{c RT}
 26. {c |} {res}2003          1          0 {txt}{c |}
 27. {c |} {res}2004          1          0 {txt}{c |}
 28. {c |} {res}2005          1          0 {txt}{c |}
 29. {c |} {res}2006          1          0 {txt}{c |}
 30. {c |} {res}2007          3          0 {txt}{c |}
     {c BLC}{hline 6}{c -}{hline 10}{c -}{hline 10}{c BRC}

{com}. 
. //Pairwise Correlation of SSR Provisions
. //Table 4
. pwcorr cease_imp  demob_imp  disarm_imp   milrfm_imp   pargrp_imp   polrfm_imp  reint_imp  with_imp,  star(.05)

             {txt}{c |} cease_~m demob_~m disarm~m milrfm~m pargrp~m polrfm~m reint_~m
{hline 13}{c +}{hline 63}
cease_implem {c |} {res}  1.0000 
{txt}demob_implem {c |} {res}  0.4096*  1.0000 
{txt}disarm_imp~m {c |} {res}  0.2566*  0.5748*  1.0000 
{txt}milrfm_imp~m {c |} {res}  0.5387*  0.5197*  0.2725*  1.0000 
{txt}pargrp_imp~m {c |} {res}  0.3799*  0.3625*  0.2796*  0.4153*  1.0000 
{txt}polrfm_imp~m {c |} {res}  0.3773*  0.4212*  0.4160*  0.4707*  0.4718*  1.0000 
{txt}reint_implem {c |} {res}  0.4145*  0.6482*  0.3901*  0.3738*  0.2471*  0.3310*  1.0000 
 {txt}with_implem {c |} {res}  0.0527  -0.0711  -0.0354  -0.0874   0.0931   0.1666* -0.1979*

             {txt}{c |} with_i~m
{hline 13}{c +}{hline 9}
 with_implem {c |} {res}  1.0000 
{txt}
{com}. 
. 
. //Generating Variables used in analysis
. gen dead_1000 = total_dead/1000
{txt}
{com}. //Generating Military reform Cumulative Variable
. gen milrfm_cum =(milrfm_implem/3)*100
{txt}
{com}. //UN Peacekeepign Implementation Rate
. gen unpkf_imprate = ( unpkf_implem/3)*100
{txt}
{com}. 
. 
. //Generating strict Security Sector Reform Variable
. //military reform, police reform, disarmament, demobilization, reintegration, paramilitary, withdrawal of troops, ceasefire
. 
. //generate SSR Provisions
. gen SSR_Prov = (cease_prov + demob_prov+ disarm_prov + milrfm_prov + pargrp_prov + polrfm_prov+ reint_prov + with_prov)
{txt}
{com}. gen SSR_Imp = (cease_imp + demob_imp + disarm_imp  + milrfm_imp  + pargrp_imp  + polrfm_imp + reint_imp  + with_imp)
{txt}
{com}. gen SSR_IMP_RateStrict = (SSR_Imp/24)*100
{txt}
{com}. gen SSR_IMP_RateLenient = (SSR_Imp/(SSR_Prov*3))*100
{txt}
{com}. 
. gen SSR_Prov_WOM =(cease_prov + demob_prov+ disarm_prov + pargrp_prov + polrfm_prov+ reint_prov + with_prov)
{txt}
{com}. gen SSR_IMP_WOM =(cease_imp + demob_imp + disarm_imp  + milrfm_imp  + pargrp_imp  + polrfm_imp + reint_imp  + with_imp)
{txt}
{com}. 
. gen SSR_IMPRate_WOMS = (SSR_IMP_WOM/21)*100
{txt}
{com}. gen SSR_IMPRate_WOML = (SSR_IMP_WOM/(SSR_Prov_WOM*3))*100
{txt}
{com}. 
. 
. //Replicate Table 5. armed conflict between signatories  
. stset year_count, id(caseid) failure( sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. 
. streg milrfm_c  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31.706058}  
Iteration 2:{space 3}log pseudolikelihood = {res:-26.416739}  
Iteration 3:{space 3}log pseudolikelihood = {res:-24.885258}  
Iteration 4:{space 3}log pseudolikelihood = {res:-24.852245}  
Iteration 5:{space 3}log pseudolikelihood = {res:-24.852144}  
Iteration 6:{space 3}log pseudolikelihood = {res:-24.852144}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}6{txt})    ={res}     71.52
{txt}Log pseudolikelihood =   {res}-24.852144                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}milrfm_cum {c |}{col 17}{res}{space 2} .0182918{col 29}{space 2} .0093379{col 40}{space 1}    1.96{col 49}{space 3}0.050{col 57}{space 4}-.0000102{col 70}{space 3} .0365937
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2} .0000388{col 29}{space 2} .0009282{col 40}{space 1}    0.04{col 49}{space 3}0.967{col 57}{space 4}-.0017804{col 70}{space 3} .0018581
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0011608{col 29}{space 2} .0042324{col 40}{space 1}   -0.27{col 49}{space 3}0.784{col 57}{space 4}-.0094561{col 70}{space 3} .0071346
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0149172{col 29}{space 2} .0106369{col 40}{space 1}   -1.40{col 49}{space 3}0.161{col 57}{space 4}-.0357651{col 70}{space 3} .0059307
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2} 1.000162{col 29}{space 2} .9308384{col 40}{space 1}    1.07{col 49}{space 3}0.283{col 57}{space 4}-.8242473{col 70}{space 3} 2.824572
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .1176744{col 29}{space 2} .0534737{col 40}{space 1}    2.20{col 49}{space 3}0.028{col 57}{space 4} .0128679{col 70}{space 3} .2224809
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  2.60587{col 29}{space 2} 1.635805{col 40}{space 1}    1.59{col 49}{space 3}0.111{col 57}{space 4}-.6002488{col 70}{space 3} 5.811989
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .3197508{col 29}{space 2} .1908462{col 40}{space 1}    1.68{col 49}{space 3}0.094{col 57}{space 4}-.0543009{col 70}{space 3} .6938025
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.376785{col 29}{space 2} .2627541{col 57}{space 4} .9471471{col 70}{space 3} 2.001311
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2}   .72633{col 29}{space 2} .1386173{col 57}{space 4} .4996724{col 70}{space 3} 1.055802
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg milrfm_c SSR_IMPRate_WOMS dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.285006}  
Iteration 2:{space 3}log pseudolikelihood = {res:-21.006069}  
Iteration 3:{space 3}log pseudolikelihood = {res:-20.072174}  
Iteration 4:{space 3}log pseudolikelihood = {res:-20.027785}  
Iteration 5:{space 3}log pseudolikelihood = {res:-20.027589}  
Iteration 6:{space 3}log pseudolikelihood = {res:-20.027589}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}    103.42
{txt}Log pseudolikelihood =   {res}-20.027589                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              _t{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}milrfm_cum {c |}{col 18}{res}{space 2}-.0006858{col 30}{space 2} .0078624{col 41}{space 1}   -0.09{col 50}{space 3}0.930{col 58}{space 4}-.0160957{col 71}{space 3} .0147242
{txt}SSR_IMPRate_WOMS {c |}{col 18}{res}{space 2} .0305476{col 30}{space 2} .0094318{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0120616{col 71}{space 3} .0490335
{txt}{space 7}dead_1000 {c |}{col 18}{res}{space 2}-.0003981{col 30}{space 2} .0004334{col 41}{space 1}   -0.92{col 50}{space 3}0.358{col 58}{space 4}-.0012476{col 71}{space 3} .0004514
{txt}{space 2}war_dur_months {c |}{col 18}{res}{space 2}-.0009328{col 30}{space 2}    .0035{col 41}{space 1}   -0.27{col 50}{space 3}0.790{col 58}{space 4}-.0077926{col 71}{space 3}  .005927
{txt}{space 5}infant_rate {c |}{col 18}{res}{space 2}-.0151605{col 30}{space 2} .0058071{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.0265421{col 71}{space 3}-.0037788
{txt}{space 3}conflict_type {c |}{col 18}{res}{space 2} .8044758{col 30}{space 2} .6075669{col 41}{space 1}    1.32{col 50}{space 3}0.185{col 58}{space 4}-.3863334{col 71}{space 3} 1.995285
{txt}{space 1}polity_2_1lag_1 {c |}{col 18}{res}{space 2}  .068898{col 30}{space 2} .0357774{col 41}{space 1}    1.93{col 50}{space 3}0.054{col 58}{space 4}-.0012244{col 71}{space 3} .1390204
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.981018{col 30}{space 2} 1.040686{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0586886{col 71}{space 3} 4.020725
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
           /ln_p {c |}{col 18}{res}{space 2} .6655334{col 30}{space 2} .2587564{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .1583803{col 71}{space 3} 1.172687
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               p{col 18}{c |}{res}{space 2} 1.945528{col 30}{space 2} .5034178{col 58}{space 4} 1.171612{col 71}{space 3}  3.23066
{col 1}{txt}             1/p{col 18}{c |}{res}{space 2} .5139993{col 30}{space 2} .1330006{col 58}{space 4} .3095342{col 71}{space 3} .8535251
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateStrict  unpkf_imprate dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.111996}  
Iteration 2:{space 3}log pseudolikelihood = {res:-20.552118}  
Iteration 3:{space 3}log pseudolikelihood = {res:-19.574478}  
Iteration 4:{space 3}log pseudolikelihood = {res:-19.525836}  
Iteration 5:{space 3}log pseudolikelihood = {res:-19.525673}  
Iteration 6:{space 3}log pseudolikelihood = {res:-19.525673}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}    112.91
{txt}Log pseudolikelihood =   {res}-19.525673                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2}  .032405{col 32}{space 2} .0072723{col 43}{space 1}    4.46{col 52}{space 3}0.000{col 60}{space 4} .0181515{col 73}{space 3} .0466585
{txt}{space 5}unpkf_imprate {c |}{col 20}{res}{space 2} .0047324{col 32}{space 2} .0049865{col 43}{space 1}    0.95{col 52}{space 3}0.343{col 60}{space 4}-.0050411{col 73}{space 3} .0145058
{txt}{space 9}dead_1000 {c |}{col 20}{res}{space 2}-.0005051{col 32}{space 2} .0004297{col 43}{space 1}   -1.18{col 52}{space 3}0.240{col 60}{space 4}-.0013474{col 73}{space 3} .0003372
{txt}{space 4}war_dur_months {c |}{col 20}{res}{space 2}-.0011017{col 32}{space 2} .0034137{col 43}{space 1}   -0.32{col 52}{space 3}0.747{col 60}{space 4}-.0077923{col 73}{space 3}  .005589
{txt}{space 7}infant_rate {c |}{col 20}{res}{space 2}-.0162553{col 32}{space 2} .0048609{col 43}{space 1}   -3.34{col 52}{space 3}0.001{col 60}{space 4}-.0257825{col 73}{space 3}-.0067281
{txt}{space 5}conflict_type {c |}{col 20}{res}{space 2} .8465724{col 32}{space 2} .7115273{col 43}{space 1}    1.19{col 52}{space 3}0.234{col 60}{space 4}-.5479955{col 73}{space 3}  2.24114
{txt}{space 3}polity_2_1lag_1 {c |}{col 20}{res}{space 2} .0861765{col 32}{space 2}  .045273{col 43}{space 1}    1.90{col 52}{space 3}0.057{col 60}{space 4} -.002557{col 73}{space 3} .1749101
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.998599{col 32}{space 2} .9207122{col 43}{space 1}    2.17{col 52}{space 3}0.030{col 60}{space 4} .1940359{col 73}{space 3} 3.803161
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2} .6730261{col 32}{space 2} .2478685{col 43}{space 1}    2.72{col 52}{space 3}0.007{col 60}{space 4} .1872127{col 73}{space 3} 1.158839
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2}  1.96016{col 32}{space 2} .4858619{col 60}{space 4} 1.205884{col 73}{space 3} 3.186233
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} .5101625{col 32}{space 2} .1264532{col 60}{space 4} .3138502{col 73}{space 3} .8292673
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //To generate Figure 6.1
. streg SSR_IMP_RateStrict  unpkf_imprate dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.111996}  
Iteration 2:{space 3}log pseudolikelihood = {res:-20.552118}  
Iteration 3:{space 3}log pseudolikelihood = {res:-19.574478}  
Iteration 4:{space 3}log pseudolikelihood = {res:-19.525836}  
Iteration 5:{space 3}log pseudolikelihood = {res:-19.525673}  
Iteration 6:{space 3}log pseudolikelihood = {res:-19.525673}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}    112.91
{txt}Log pseudolikelihood =   {res}-19.525673                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2}  .032405{col 32}{space 2} .0072723{col 43}{space 1}    4.46{col 52}{space 3}0.000{col 60}{space 4} .0181515{col 73}{space 3} .0466585
{txt}{space 5}unpkf_imprate {c |}{col 20}{res}{space 2} .0047324{col 32}{space 2} .0049865{col 43}{space 1}    0.95{col 52}{space 3}0.343{col 60}{space 4}-.0050411{col 73}{space 3} .0145058
{txt}{space 9}dead_1000 {c |}{col 20}{res}{space 2}-.0005051{col 32}{space 2} .0004297{col 43}{space 1}   -1.18{col 52}{space 3}0.240{col 60}{space 4}-.0013474{col 73}{space 3} .0003372
{txt}{space 4}war_dur_months {c |}{col 20}{res}{space 2}-.0011017{col 32}{space 2} .0034137{col 43}{space 1}   -0.32{col 52}{space 3}0.747{col 60}{space 4}-.0077923{col 73}{space 3}  .005589
{txt}{space 7}infant_rate {c |}{col 20}{res}{space 2}-.0162553{col 32}{space 2} .0048609{col 43}{space 1}   -3.34{col 52}{space 3}0.001{col 60}{space 4}-.0257825{col 73}{space 3}-.0067281
{txt}{space 5}conflict_type {c |}{col 20}{res}{space 2} .8465724{col 32}{space 2} .7115273{col 43}{space 1}    1.19{col 52}{space 3}0.234{col 60}{space 4}-.5479955{col 73}{space 3}  2.24114
{txt}{space 3}polity_2_1lag_1 {c |}{col 20}{res}{space 2} .0861765{col 32}{space 2}  .045273{col 43}{space 1}    1.90{col 52}{space 3}0.057{col 60}{space 4} -.002557{col 73}{space 3} .1749101
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.998599{col 32}{space 2} .9207122{col 43}{space 1}    2.17{col 52}{space 3}0.030{col 60}{space 4} .1940359{col 73}{space 3} 3.803161
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2} .6730261{col 32}{space 2} .2478685{col 43}{space 1}    2.72{col 52}{space 3}0.007{col 60}{space 4} .1872127{col 73}{space 3} 1.158839
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2}  1.96016{col 32}{space 2} .4858619{col 60}{space 4} 1.205884{col 73}{space 3} 3.186233
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} .5101625{col 32}{space 2} .1264532{col 60}{space 4} .3138502{col 73}{space 3} .8292673
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. stcurve, survival at1(SSR_IMP_RateStrict=0) at2(SSR_IMP_RateStrict=25) at3(SSR_IMP_RateStrict=50) at4(SSR_IMP_RateStrict=75)
{res}{txt}
{com}. //graph save "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\Figure6.1.gph" 
. 
. 
. //Replicate Table 5. armed conflict between non-signatories
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(nonsig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}nonsig_minor_war != 0 & nonsig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       79{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      227{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       11{txt}  failures in single failure-per-subject data
{res}      227{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. 
. streg milrfm_c  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34.738032}  
Iteration 2:{space 3}log pseudolikelihood = {res:-33.771379}  
Iteration 3:{space 3}log pseudolikelihood = {res: -33.76621}  
Iteration 4:{space 3}log pseudolikelihood = {res:-33.766209}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}6{txt})    ={res}     15.63
{txt}Log pseudolikelihood =   {res}-33.766209                {txt}Prob > chi2     ={res}    0.0159

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}milrfm_cum {c |}{col 17}{res}{space 2} .0042431{col 29}{space 2}  .008435{col 40}{space 1}    0.50{col 49}{space 3}0.615{col 57}{space 4}-.0122892{col 70}{space 3} .0207754
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2} .0008268{col 29}{space 2} .0012497{col 40}{space 1}    0.66{col 49}{space 3}0.508{col 57}{space 4}-.0016226{col 70}{space 3} .0032763
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0018138{col 29}{space 2} .0046826{col 40}{space 1}   -0.39{col 49}{space 3}0.699{col 57}{space 4}-.0109914{col 70}{space 3} .0073639
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2} -.029933{col 29}{space 2} .0143518{col 40}{space 1}   -2.09{col 49}{space 3}0.037{col 57}{space 4} -.058062{col 70}{space 3}-.0018039
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2}-.9460656{col 29}{space 2} 1.047398{col 40}{space 1}   -0.90{col 49}{space 3}0.366{col 57}{space 4}-2.998928{col 70}{space 3} 1.106796
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .0291508{col 29}{space 2} .0789036{col 40}{space 1}    0.37{col 49}{space 3}0.712{col 57}{space 4}-.1254974{col 70}{space 3}  .183799
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  5.68355{col 29}{space 2}  2.02404{col 40}{space 1}    2.81{col 49}{space 3}0.005{col 57}{space 4} 1.716504{col 70}{space 3} 9.650595
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2}-.1690711{col 29}{space 2} .1990091{col 40}{space 1}   -0.85{col 49}{space 3}0.396{col 57}{space 4}-.5591217{col 70}{space 3} .2209794
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} .8444488{col 29}{space 2}  .168053{col 57}{space 4}  .571711{col 70}{space 3} 1.247298
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2} 1.184204{col 29}{space 2} .2356674{col 57}{space 4} .8017332{col 70}{space 3} 1.749136
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg milrfm_c SSR_IMPRate_WOMS dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-35.942468}  
Iteration 2:{space 3}log pseudolikelihood = {res: -27.13118}  
Iteration 3:{space 3}log pseudolikelihood = {res:-26.975281}  
Iteration 4:{space 3}log pseudolikelihood = {res:-26.971938}  
Iteration 5:{space 3}log pseudolikelihood = {res:-26.971936}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     50.13
{txt}Log pseudolikelihood =   {res}-26.971936                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}              _t{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}milrfm_cum {c |}{col 18}{res}{space 2}-.0235273{col 30}{space 2} .0123546{col 41}{space 1}   -1.90{col 50}{space 3}0.057{col 58}{space 4}-.0477419{col 71}{space 3} .0006874
{txt}SSR_IMPRate_WOMS {c |}{col 18}{res}{space 2} .0786474{col 30}{space 2} .0257724{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0281345{col 71}{space 3} .1291603
{txt}{space 7}dead_1000 {c |}{col 18}{res}{space 2}  .000179{col 30}{space 2} .0007664{col 41}{space 1}    0.23{col 50}{space 3}0.815{col 58}{space 4}-.0013231{col 71}{space 3} .0016812
{txt}{space 2}war_dur_months {c |}{col 18}{res}{space 2} .0005129{col 30}{space 2}   .00413{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4}-.0075817{col 71}{space 3} .0086075
{txt}{space 5}infant_rate {c |}{col 18}{res}{space 2}-.0097841{col 30}{space 2}  .007946{col 41}{space 1}   -1.23{col 50}{space 3}0.218{col 58}{space 4} -.025358{col 71}{space 3} .0057898
{txt}{space 3}conflict_type {c |}{col 18}{res}{space 2} .4177093{col 30}{space 2} .9965962{col 41}{space 1}    0.42{col 50}{space 3}0.675{col 58}{space 4}-1.535583{col 71}{space 3} 2.371002
{txt}{space 1}polity_2_1lag_1 {c |}{col 18}{res}{space 2}-.0180257{col 30}{space 2} .0599933{col 41}{space 1}   -0.30{col 50}{space 3}0.764{col 58}{space 4}-.1356103{col 71}{space 3}  .099559
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.198272{col 30}{space 2} 1.589343{col 41}{space 1}    0.75{col 50}{space 3}0.451{col 58}{space 4}-1.916784{col 71}{space 3} 4.313328
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
           /ln_p {c |}{col 18}{res}{space 2} .1234618{col 30}{space 2} .2832168{col 41}{space 1}    0.44{col 50}{space 3}0.663{col 58}{space 4}-.4316329{col 71}{space 3} .6785564
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               p{col 18}{c |}{res}{space 2} 1.131407{col 30}{space 2} .3204333{col 58}{space 4} .6494478{col 71}{space 3}  1.97103
{col 1}{txt}             1/p{col 18}{c |}{res}{space 2} .8838554{col 30}{space 2} .2503227{col 58}{space 4} .5073489{col 71}{space 3}  1.53977
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateStrict  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34.914761}  
Iteration 2:{space 3}log pseudolikelihood = {res: -29.37618}  
Iteration 3:{space 3}log pseudolikelihood = {res: -29.28907}  
Iteration 4:{space 3}log pseudolikelihood = {res: -29.28874}  
Iteration 5:{space 3}log pseudolikelihood = {res: -29.28874}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     49.18
{txt}Log pseudolikelihood =   {res} -29.28874                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2} .0539471{col 32}{space 2} .0209241{col 43}{space 1}    2.58{col 52}{space 3}0.010{col 60}{space 4} .0129366{col 73}{space 3} .0949575
{txt}{space 5}unpkf_imprate {c |}{col 20}{res}{space 2}-.0010047{col 32}{space 2} .0087977{col 43}{space 1}   -0.11{col 52}{space 3}0.909{col 60}{space 4}-.0182479{col 73}{space 3} .0162386
{txt}{space 9}dead_1000 {c |}{col 20}{res}{space 2} .0001325{col 32}{space 2} .0008378{col 43}{space 1}    0.16{col 52}{space 3}0.874{col 60}{space 4}-.0015096{col 73}{space 3} .0017745
{txt}{space 4}war_dur_months {c |}{col 20}{res}{space 2} .0002267{col 32}{space 2} .0045042{col 43}{space 1}    0.05{col 52}{space 3}0.960{col 60}{space 4}-.0086012{col 73}{space 3} .0090547
{txt}{space 7}infant_rate {c |}{col 20}{res}{space 2}-.0149751{col 32}{space 2} .0118673{col 43}{space 1}   -1.26{col 52}{space 3}0.207{col 60}{space 4}-.0382347{col 73}{space 3} .0082844
{txt}{space 5}conflict_type {c |}{col 20}{res}{space 2}-.2991237{col 32}{space 2} .9449116{col 43}{space 1}   -0.32{col 52}{space 3}0.752{col 60}{space 4}-2.151116{col 73}{space 3} 1.552869
{txt}{space 3}polity_2_1lag_1 {c |}{col 20}{res}{space 2} .0248306{col 32}{space 2} .0751192{col 43}{space 1}    0.33{col 52}{space 3}0.741{col 60}{space 4}-.1224003{col 73}{space 3} .1720615
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.220842{col 32}{space 2} 2.199295{col 43}{space 1}    1.01{col 52}{space 3}0.313{col 60}{space 4}-2.089696{col 73}{space 3} 6.531381
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2} .0415893{col 32}{space 2}  .212058{col 43}{space 1}    0.20{col 52}{space 3}0.845{col 60}{space 4}-.3740367{col 73}{space 3} .4572153
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2} 1.042466{col 32}{space 2} .2210633{col 60}{space 4} .6879516{col 73}{space 3} 1.579669
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} .9592637{col 32}{space 2} .2034195{col 60}{space 4}  .633044{col 73}{space 3} 1.453591
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //to generate Figure 6.2 
. streg SSR_IMP_RateStrict  dead_1000  unpkf_imprate  war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34.914761}  
Iteration 2:{space 3}log pseudolikelihood = {res: -29.37618}  
Iteration 3:{space 3}log pseudolikelihood = {res: -29.28907}  
Iteration 4:{space 3}log pseudolikelihood = {res: -29.28874}  
Iteration 5:{space 3}log pseudolikelihood = {res: -29.28874}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     49.18
{txt}Log pseudolikelihood =   {res} -29.28874                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2} .0539471{col 32}{space 2} .0209241{col 43}{space 1}    2.58{col 52}{space 3}0.010{col 60}{space 4} .0129366{col 73}{space 3} .0949575
{txt}{space 9}dead_1000 {c |}{col 20}{res}{space 2} .0001325{col 32}{space 2} .0008378{col 43}{space 1}    0.16{col 52}{space 3}0.874{col 60}{space 4}-.0015096{col 73}{space 3} .0017745
{txt}{space 5}unpkf_imprate {c |}{col 20}{res}{space 2}-.0010047{col 32}{space 2} .0087977{col 43}{space 1}   -0.11{col 52}{space 3}0.909{col 60}{space 4}-.0182479{col 73}{space 3} .0162386
{txt}{space 4}war_dur_months {c |}{col 20}{res}{space 2} .0002267{col 32}{space 2} .0045042{col 43}{space 1}    0.05{col 52}{space 3}0.960{col 60}{space 4}-.0086012{col 73}{space 3} .0090547
{txt}{space 7}infant_rate {c |}{col 20}{res}{space 2}-.0149751{col 32}{space 2} .0118673{col 43}{space 1}   -1.26{col 52}{space 3}0.207{col 60}{space 4}-.0382347{col 73}{space 3} .0082844
{txt}{space 5}conflict_type {c |}{col 20}{res}{space 2}-.2991237{col 32}{space 2} .9449116{col 43}{space 1}   -0.32{col 52}{space 3}0.752{col 60}{space 4}-2.151116{col 73}{space 3} 1.552869
{txt}{space 3}polity_2_1lag_1 {c |}{col 20}{res}{space 2} .0248306{col 32}{space 2} .0751192{col 43}{space 1}    0.33{col 52}{space 3}0.741{col 60}{space 4}-.1224003{col 73}{space 3} .1720615
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.220842{col 32}{space 2} 2.199295{col 43}{space 1}    1.01{col 52}{space 3}0.313{col 60}{space 4}-2.089696{col 73}{space 3} 6.531381
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2} .0415893{col 32}{space 2}  .212058{col 43}{space 1}    0.20{col 52}{space 3}0.845{col 60}{space 4}-.3740367{col 73}{space 3} .4572153
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2} 1.042466{col 32}{space 2} .2210633{col 60}{space 4} .6879516{col 73}{space 3} 1.579669
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} .9592637{col 32}{space 2} .2034195{col 60}{space 4}  .633044{col 73}{space 3} 1.453591
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. stcurve, survival at1(SSR_IMP_RateStrict=0) at2(SSR_IMP_RateStrict=25) at3(SSR_IMP_RateStrict=50) at4(SSR_IMP_RateStrict=75)
{res}{txt}
{com}. //graph save "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\Figure6.2.gph", replace 
. 
{txt}end of do-file

{com}. do "C:\Users\MJOSHI~1.DSS\AppData\Local\Temp\STD04000000.tmp"
{txt}
{com}. //Generate Data for Figure 4
. gen total_prov = (amnest_prov + arbdamprov + arbland_prov + bound_prov + cease_prov  + child_prov + citiz_prov + civadm_prov + const_prov + cultr_prov + decen_prov + demob_prov + develop_prov + disarm_prov + disput_prov + donor_prov + educat_prov + elect_prov + embarg_prov + ethrel_prov + exerefm_prov + humrts_prov + idps_prov + indmin_prov + indrefer_prov + judrfm_prov + legref_prov + media_prov + milrfm_prov + minrts_prov + natres_prov + offlan_prov + pargrp_prov + polrfm_prov + powtran_prov  + prisr_prov + ratm_prov + refug_prov + regpkf_prov + reint_prov + repar_prov + roa_prov +selfd_prov + terpow_prov + time_prov + truth_prov + unpkf_prov + untran_prov + verify_prov + with_prov + women_prov )  
{txt}
{com}. 
. gen total_imp = (amnest_implem + arbdam_implem+ arbland_implem+ bound_implem+ cease_implem+ child_implem+ citiz_implem+ civadm_impem+ const_implem+ cultr_implem + decen_implem + demob_implem + develop_iplem + disarm_implem + dispute_implem + donor_implem + educat_implem + elect_implem + embarg_implem + ethrel_implem + exerefm_implem + humrts_implem + idps_implem + indmin_implem + indrefer_implem + judrfm_implem + legref_implem + media_implem + milrfm_implem + minrts_implem + natres_implem + offlan_implem + pargrp_implem + polrfm_implem + powtran_implem + prisr_implem + ratm_implem + refug_implem + regpkf_implem + reint_implem + repar_implem + roa_implem + selfd_implem + terpow_implem + time_implem + truth_implem + unpkf_implem + untran_implem + verify_implem + with_implem + women_implem)
{txt}
{com}. gen agg_imp_rate = (total_imp/ (total_prov*3))*100
{txt}
{com}. 
. gen guatemala_imprate = .
{txt}(340 missing values generated)

{com}. replace guatemala_imprate= agg_imp_rate if caseid==1
{txt}(10 real changes made)

{com}. 
. gen nireland_imprate = .
{txt}(340 missing values generated)

{com}. replace nireland_imprate= agg_imp_rate if caseid==3
{txt}(10 real changes made)

{com}. 
. gen mali_imprate = .
{txt}(340 missing values generated)

{com}. replace mali_imprate= agg_imp_rate if caseid==8
{txt}(10 real changes made)

{com}. 
. gen niger_imprate = .
{txt}(340 missing values generated)

{com}. replace niger_imprate= agg_imp_rate if caseid==10
{txt}(10 real changes made)

{com}. 
. gen lebanon_imprate= .
{txt}(340 missing values generated)

{com}. replace lebanon_imprate= agg_imp_rate if caseid==25
{txt}(10 real changes made)

{com}. 
. gen nepal_imprate = .
{txt}(340 missing values generated)

{com}. replace nepal_imprate= agg_imp_rate if caseid==29
{txt}(10 real changes made)

{com}. 
{txt}end of do-file

{com}. do "C:\Users\MJOSHI~1.DSS\AppData\Local\Temp\STD04000000.tmp"
{txt}
{com}. line  guatemala_imprate year_count if  exclude_cases!=1 & caseid==1, title("Guatemala")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case1.gph", replace
. 
. line  nireland_imprate year_count if  exclude_cases!=1 & caseid==3, title("Northern Ireland")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case3.gph", replace
. 
. line  mali_imprate year_count if  exclude_cases!=1 & caseid==8, title("Mali")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case8.gph", replace
. 
. line  niger_imprate year_count if  exclude_cases!=1 & caseid==10, title("Niger")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case10.gph", replace
. 
. line  agg_imp_rate year_count if  exclude_cases!=1 & caseid==25, title("Lebanon")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case25.gph", replace
. 
. line  agg_imp_rate year_count if  exclude_cases!=1 & caseid==29, title("Nepal")
{res}{txt}
{com}. //graph save Graph "C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\Replication Files\case29.gph", replace
. 
{txt}end of do-file

{com}. do "C:\Users\MJOSHI~1.DSS\AppData\Local\Temp\STD04000000.tmp"
{txt}
{com}. //Generate Data to Replicate Figure 5 
. //Generated Data & Figure in Excel File
. count if SSR_Prov==2 & year_count==1
{res}    2
{txt}
{com}. count if SSR_Prov==3 & year_count==1
{res}    4
{txt}
{com}. count if SSR_Prov==4 & year_count==1
{res}    2
{txt}
{com}. count if SSR_Prov==5 & year_count==1
{res}    8
{txt}
{com}. count if SSR_Prov==6 & year_count==1
{res}    6
{txt}
{com}. count if SSR_Prov==7 & year_count==1
{res}    7
{txt}
{com}. count if SSR_Prov==8 & year_count==1
{res}    5
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\MJOSHI~1.DSS\AppData\Local\Temp\STD04000000.tmp"
{txt}
{com}. ///////////END OF DO FILES for Table & Figures in PAPER///////////
> 
. 
. 
. //Appendix
. //Between Signatories
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. 
. streg SSR_IMP_RateStrict if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-37.040809
{txt}Iteration 1:   log pseudolikelihood = {res}-35.789805
{txt}Iteration 2:   log pseudolikelihood = {res}-35.731554
{txt}Iteration 3:   log pseudolikelihood = {res}-35.731434
{txt}Iteration 4:   log pseudolikelihood = {res}-35.731434

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.731434}  
Iteration 1:{space 3}log pseudolikelihood = {res:-32.263437}  
Iteration 2:{space 3}log pseudolikelihood = {res:-31.512929}  
Iteration 3:{space 3}log pseudolikelihood = {res:-31.502913}  
Iteration 4:{space 3}log pseudolikelihood = {res:-31.502906}  
Iteration 5:{space 3}log pseudolikelihood = {res:-31.502906}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       225
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         225
                                                   {txt}Wald chi2({res}1{txt})    ={res}      6.78
{txt}Log pseudolikelihood =   {res}-31.502906                {txt}Prob > chi2     ={res}    0.0092

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2} .0623778{col 32}{space 2} .0239613{col 43}{space 1}    2.60{col 52}{space 3}0.009{col 60}{space 4} .0154145{col 73}{space 3} .1093411
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  1.24672{col 32}{space 2}  .751677{col 43}{space 1}    1.66{col 52}{space 3}0.097{col 60}{space 4}-.2265395{col 73}{space 3}  2.71998
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2}-.2575211{col 32}{space 2} .1189889{col 43}{space 1}   -2.16{col 52}{space 3}0.030{col 60}{space 4}-.4907351{col 73}{space 3}-.0243071
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2} .7729653{col 32}{space 2} .0919743{col 60}{space 4} .6121762{col 73}{space 3} .9759859
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} 1.293719{col 32}{space 2} .1539382{col 60}{space 4} 1.024605{col 73}{space 3} 1.633517
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateLenient if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-37.040809
{txt}Iteration 1:   log pseudolikelihood = {res}-35.789805
{txt}Iteration 2:   log pseudolikelihood = {res}-35.731554
{txt}Iteration 3:   log pseudolikelihood = {res}-35.731434
{txt}Iteration 4:   log pseudolikelihood = {res}-35.731434

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.731434}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34.898636}  
Iteration 2:{space 3}log pseudolikelihood = {res:-30.146637}  
Iteration 3:{space 3}log pseudolikelihood = {res:-30.070588}  
Iteration 4:{space 3}log pseudolikelihood = {res:-30.070309}  
Iteration 5:{space 3}log pseudolikelihood = {res:-30.070309}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       225
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         225
                                                   {txt}Wald chi2({res}1{txt})    ={res}     13.06
{txt}Log pseudolikelihood =   {res}-30.070309                {txt}Prob > chi2     ={res}    0.0003

{txt}{ralign 85:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}                 _t{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      z{col 53}   P>|z|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateLenient {c |}{col 21}{res}{space 2} .0470681{col 33}{space 2} .0130256{col 44}{space 1}    3.61{col 53}{space 3}0.000{col 61}{space 4} .0215385{col 74}{space 3} .0725978
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .6495165{col 33}{space 2} .6266639{col 44}{space 1}    1.04{col 53}{space 3}0.300{col 61}{space 4}-.5787223{col 74}{space 3} 1.877755
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              /ln_p {c |}{col 21}{res}{space 2}-.1385537{col 33}{space 2} .1252697{col 44}{space 1}   -1.11{col 53}{space 3}0.269{col 61}{space 4}-.3840778{col 74}{space 3} .1069704
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  p{col 21}{c |}{res}{space 2} .8706165{col 33}{space 2} .1090619{col 61}{space 4} .6810784{col 74}{space 3} 1.112901
{col 1}{txt}                1/p{col 21}{c |}{res}{space 2} 1.148611{col 33}{space 2} .1438862{col 61}{space 4} .8985523{col 74}{space 3}  1.46826
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateLenient unpkf_imprate dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31.833722}  
Iteration 2:{space 3}log pseudolikelihood = {res:-30.389215}  
Iteration 3:{space 3}log pseudolikelihood = {res:-21.325099}  
Iteration 4:{space 3}log pseudolikelihood = {res:-21.115893}  
Iteration 5:{space 3}log pseudolikelihood = {res:-21.112842}  
Iteration 6:{space 3}log pseudolikelihood = {res:-21.112841}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}     90.78
{txt}Log pseudolikelihood =   {res}-21.112841                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 85:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}                 _t{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      z{col 53}   P>|z|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateLenient {c |}{col 21}{res}{space 2}  .028521{col 33}{space 2} .0063037{col 44}{space 1}    4.52{col 53}{space 3}0.000{col 61}{space 4}  .016166{col 74}{space 3}  .040876
{txt}{space 6}unpkf_imprate {c |}{col 21}{res}{space 2} .0066595{col 33}{space 2} .0050395{col 44}{space 1}    1.32{col 53}{space 3}0.186{col 61}{space 4}-.0032176{col 74}{space 3} .0165367
{txt}{space 10}dead_1000 {c |}{col 21}{res}{space 2}-.0003002{col 33}{space 2}  .000473{col 44}{space 1}   -0.63{col 53}{space 3}0.526{col 61}{space 4}-.0012272{col 74}{space 3} .0006268
{txt}{space 5}war_dur_months {c |}{col 21}{res}{space 2}-.0017187{col 33}{space 2} .0032737{col 44}{space 1}   -0.53{col 53}{space 3}0.600{col 61}{space 4}-.0081351{col 74}{space 3} .0046977
{txt}{space 8}infant_rate {c |}{col 21}{res}{space 2}-.0109784{col 33}{space 2} .0059915{col 44}{space 1}   -1.83{col 53}{space 3}0.067{col 61}{space 4}-.0227216{col 74}{space 3} .0007648
{txt}{space 6}conflict_type {c |}{col 21}{res}{space 2} .6559042{col 33}{space 2} .5868239{col 44}{space 1}    1.12{col 53}{space 3}0.264{col 61}{space 4}-.4942495{col 74}{space 3} 1.806058
{txt}{space 4}polity_2_1lag_1 {c |}{col 21}{res}{space 2} .1144505{col 33}{space 2} .0377841{col 44}{space 1}    3.03{col 53}{space 3}0.002{col 61}{space 4}  .040395{col 74}{space 3}  .188506
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 1.265316{col 33}{space 2} 1.062407{col 44}{space 1}    1.19{col 53}{space 3}0.234{col 61}{space 4}-.8169632{col 74}{space 3} 3.347595
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              /ln_p {c |}{col 21}{res}{space 2} .6095779{col 33}{space 2} .2575192{col 44}{space 1}    2.37{col 53}{space 3}0.018{col 61}{space 4} .1048496{col 74}{space 3} 1.114306
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  p{col 21}{c |}{res}{space 2} 1.839655{col 33}{space 2} .4737464{col 61}{space 4} 1.110544{col 74}{space 3} 3.047453
{col 1}{txt}                1/p{col 21}{c |}{res}{space 2} .5435803{col 33}{space 2} .1399823{col 61}{space 4} .3281429{col 74}{space 3}   .90046
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. //Between non_signatories
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(nonsig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}nonsig_minor_war != 0 & nonsig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       79{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      227{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       11{txt}  failures in single failure-per-subject data
{res}      227{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. 
. streg SSR_IMP_RateStrict if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-39.135822
{txt}Iteration 1:   log pseudolikelihood = {res}-37.896411
{txt}Iteration 2:   log pseudolikelihood = {res}-37.850116
{txt}Iteration 3:   log pseudolikelihood = {res}-37.850052
{txt}Iteration 4:   log pseudolikelihood = {res}-37.850052

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.850052}  
Iteration 1:{space 3}log pseudolikelihood = {res:-33.058144}  
Iteration 2:{space 3}log pseudolikelihood = {res:-31.743199}  
Iteration 3:{space 3}log pseudolikelihood = {res:-31.726946}  
Iteration 4:{space 3}log pseudolikelihood = {res:-31.726933}  
Iteration 5:{space 3}log pseudolikelihood = {res:-31.726933}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       215
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         215
                                                   {txt}Wald chi2({res}1{txt})    ={res}     16.06
{txt}Log pseudolikelihood =   {res}-31.726933                {txt}Prob > chi2     ={res}    0.0001

{txt}{ralign 84:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}                _t{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateStrict {c |}{col 20}{res}{space 2} .0709786{col 32}{space 2} .0177132{col 43}{space 1}    4.01{col 52}{space 3}0.000{col 60}{space 4} .0362614{col 73}{space 3} .1056958
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .7144893{col 32}{space 2} .6800734{col 43}{space 1}    1.05{col 52}{space 3}0.293{col 60}{space 4}-.6184301{col 73}{space 3} 2.047409
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /ln_p {c |}{col 20}{res}{space 2}-.1562328{col 32}{space 2} .1626803{col 43}{space 1}   -0.96{col 52}{space 3}0.337{col 60}{space 4}-.4750803{col 73}{space 3} .1626148
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 p{col 20}{c |}{res}{space 2} .8553601{col 32}{space 2} .1391502{col 60}{space 4} .6218351{col 73}{space 3} 1.176583
{col 1}{txt}               1/p{col 20}{c |}{res}{space 2} 1.169098{col 32}{space 2} .1901893{col 60}{space 4} .8499185{col 73}{space 3} 1.608143
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateLenient if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-39.135822
{txt}Iteration 1:   log pseudolikelihood = {res}-37.896411
{txt}Iteration 2:   log pseudolikelihood = {res}-37.850116
{txt}Iteration 3:   log pseudolikelihood = {res}-37.850052
{txt}Iteration 4:   log pseudolikelihood = {res}-37.850052

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.850052}  
Iteration 1:{space 3}log pseudolikelihood = {res:-30.656102}  
Iteration 2:{space 3}log pseudolikelihood = {res:-28.957685}  
Iteration 3:{space 3}log pseudolikelihood = {res:-28.905349}  
Iteration 4:{space 3}log pseudolikelihood = {res:-28.905172}  
Iteration 5:{space 3}log pseudolikelihood = {res:-28.905172}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       215
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         215
                                                   {txt}Wald chi2({res}1{txt})    ={res}     35.03
{txt}Log pseudolikelihood =   {res}-28.905172                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 85:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}                 _t{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      z{col 53}   P>|z|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateLenient {c |}{col 21}{res}{space 2} .0511121{col 33}{space 2} .0086364{col 44}{space 1}    5.92{col 53}{space 3}0.000{col 61}{space 4} .0341851{col 74}{space 3} .0680392
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1898408{col 33}{space 2} .5064408{col 44}{space 1}    0.37{col 53}{space 3}0.708{col 61}{space 4}-.8027649{col 74}{space 3} 1.182446
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              /ln_p {c |}{col 21}{res}{space 2} .0121918{col 33}{space 2} .1924256{col 44}{space 1}    0.06{col 53}{space 3}0.949{col 61}{space 4}-.3649555{col 74}{space 3}  .389339
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  p{col 21}{c |}{res}{space 2} 1.012266{col 33}{space 2}  .194786{col 61}{space 4} .6942275{col 74}{space 3} 1.476005
{col 1}{txt}                1/p{col 21}{c |}{res}{space 2} .9878823{col 33}{space 2} .1900938{col 61}{space 4} .6775045{col 74}{space 3}  1.44045
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. streg SSR_IMP_RateLenient unpkf_imprate dead_1000   war_dur  infant_rate conflict_type polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-29.184206}  
Iteration 2:{space 3}log pseudolikelihood = {res:-27.046484}  
Iteration 3:{space 3}log pseudolikelihood = {res:-26.916326}  
Iteration 4:{space 3}log pseudolikelihood = {res:-26.915732}  
Iteration 5:{space 3}log pseudolikelihood = {res:-26.915732}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     53.70
{txt}Log pseudolikelihood =   {res}-26.915732                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 85:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}                 _t{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      z{col 53}   P>|z|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_RateLenient {c |}{col 21}{res}{space 2} .0460472{col 33}{space 2} .0152519{col 44}{space 1}    3.02{col 53}{space 3}0.003{col 61}{space 4}  .016154{col 74}{space 3} .0759405
{txt}{space 6}unpkf_imprate {c |}{col 21}{res}{space 2}-.0006994{col 33}{space 2} .0070287{col 44}{space 1}   -0.10{col 53}{space 3}0.921{col 61}{space 4}-.0144754{col 74}{space 3} .0130765
{txt}{space 10}dead_1000 {c |}{col 21}{res}{space 2}-.0000266{col 33}{space 2} .0009879{col 44}{space 1}   -0.03{col 53}{space 3}0.978{col 61}{space 4}-.0019628{col 74}{space 3} .0019095
{txt}{space 5}war_dur_months {c |}{col 21}{res}{space 2} .0030867{col 33}{space 2} .0058364{col 44}{space 1}    0.53{col 53}{space 3}0.597{col 61}{space 4}-.0083525{col 74}{space 3} .0145259
{txt}{space 8}infant_rate {c |}{col 21}{res}{space 2}-.0019924{col 33}{space 2} .0125297{col 44}{space 1}   -0.16{col 53}{space 3}0.874{col 61}{space 4}-.0265502{col 74}{space 3} .0225653
{txt}{space 6}conflict_type {c |}{col 21}{res}{space 2}-.3260601{col 33}{space 2} .9083142{col 44}{space 1}   -0.36{col 53}{space 3}0.720{col 61}{space 4}-2.106323{col 74}{space 3} 1.454203
{txt}{space 4}polity_2_1lag_1 {c |}{col 21}{res}{space 2}  .040989{col 33}{space 2} .0905118{col 44}{space 1}    0.45{col 53}{space 3}0.651{col 61}{space 4} -.136411{col 74}{space 3} .2183889
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1543122{col 33}{space 2} 2.238954{col 44}{space 1}    0.07{col 53}{space 3}0.945{col 61}{space 4}-4.233956{col 74}{space 3} 4.542581
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              /ln_p {c |}{col 21}{res}{space 2} .1474784{col 33}{space 2} .2028581{col 44}{space 1}    0.73{col 53}{space 3}0.467{col 61}{space 4}-.2501163{col 74}{space 3}  .545073
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  p{col 21}{c |}{res}{space 2} 1.158908{col 33}{space 2} .2350939{col 61}{space 4} .7787102{col 74}{space 3} 1.724734
{col 1}{txt}                1/p{col 21}{c |}{res}{space 2} .8628811{col 33}{space 2} .1750424{col 61}{space 4} .5797995{col 74}{space 3} 1.284175
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. drop  _st _d _t _t0
{txt}
{com}. 
. //REPLICATION OF Model 3 & 6  without withdrawal implementation in the index - refers to table in Manuscript in RR1
. gen SSR_Prov_wotw = (cease_prov + demob_prov+ disarm_prov + milrfm_prov + pargrp_prov + polrfm_prov+ reint_prov)
{txt}
{com}. gen SSR_Imp_wotw = (cease_imp + demob_imp + disarm_imp  + milrfm_imp  + pargrp_imp  + polrfm_imp + reint_imp)
{txt}
{com}. gen SSR_IMP_Rate_wotw = (SSR_Imp_wotw/21)*100
{txt}
{com}. 
. //between signatories
. 
. stset year_count, id(caseid) failure(sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. stset year_count, id(caseid) failure( sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_Rate_wotw  unpkf_imprate dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.570838}  
Iteration 2:{space 3}log pseudolikelihood = {res:-20.974073}  
Iteration 3:{space 3}log pseudolikelihood = {res:-20.088694}  
Iteration 4:{space 3}log pseudolikelihood = {res:-20.052369}  
Iteration 5:{space 3}log pseudolikelihood = {res:-20.052281}  
Iteration 6:{space 3}log pseudolikelihood = {res:-20.052281}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}     96.18
{txt}Log pseudolikelihood =   {res}-20.052281                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 83:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}               _t{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_Rate_wotw {c |}{col 19}{res}{space 2} .0293446{col 31}{space 2} .0069812{col 42}{space 1}    4.20{col 51}{space 3}0.000{col 59}{space 4} .0156617{col 72}{space 3} .0430276
{txt}{space 4}unpkf_imprate {c |}{col 19}{res}{space 2} .0061318{col 31}{space 2} .0050963{col 42}{space 1}    1.20{col 51}{space 3}0.229{col 59}{space 4}-.0038567{col 72}{space 3} .0161203
{txt}{space 8}dead_1000 {c |}{col 19}{res}{space 2}-.0003375{col 31}{space 2} .0004041{col 42}{space 1}   -0.84{col 51}{space 3}0.404{col 59}{space 4}-.0011296{col 72}{space 3} .0004546
{txt}{space 3}war_dur_months {c |}{col 19}{res}{space 2}-.0018893{col 31}{space 2} .0034031{col 42}{space 1}   -0.56{col 51}{space 3}0.579{col 59}{space 4}-.0085593{col 72}{space 3} .0047807
{txt}{space 6}infant_rate {c |}{col 19}{res}{space 2}-.0176803{col 31}{space 2} .0051604{col 42}{space 1}   -3.43{col 51}{space 3}0.001{col 59}{space 4}-.0277944{col 72}{space 3}-.0075662
{txt}{space 4}conflict_type {c |}{col 19}{res}{space 2} .7254147{col 31}{space 2} .7176983{col 42}{space 1}    1.01{col 51}{space 3}0.312{col 59}{space 4}-.6812482{col 72}{space 3} 2.132077
{txt}{space 2}polity_2_1lag_1 {c |}{col 19}{res}{space 2} .0838985{col 31}{space 2} .0487406{col 42}{space 1}    1.72{col 51}{space 3}0.085{col 59}{space 4}-.0116313{col 72}{space 3} .1794284
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} 2.300062{col 31}{space 2} .9416779{col 42}{space 1}    2.44{col 51}{space 3}0.015{col 59}{space 4} .4544072{col 72}{space 3} 4.145717
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
            /ln_p {c |}{col 19}{res}{space 2} .6492989{col 31}{space 2} .2655487{col 42}{space 1}    2.45{col 51}{space 3}0.014{col 59}{space 4}  .128833{col 72}{space 3} 1.169765
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                p{col 19}{c |}{res}{space 2} 1.914198{col 31}{space 2} .5083129{col 59}{space 4}   1.1375{col 72}{space 3} 3.221235
{col 1}{txt}              1/p{col 19}{c |}{res}{space 2} .5224119{col 31}{space 2} .1387258{col 59}{space 4} .3104399{col 72}{space 3} .8791208
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //between non-signatories
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(nonsig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}nonsig_minor_war != 0 & nonsig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       79{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      227{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       11{txt}  failures in single failure-per-subject data
{res}      227{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_Rate_wotw  unpkf_imprate dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34.953707}  
Iteration 2:{space 3}log pseudolikelihood = {res:-30.503663}  
Iteration 3:{space 3}log pseudolikelihood = {res:-30.457509}  
Iteration 4:{space 3}log pseudolikelihood = {res:-30.457381}  
Iteration 5:{space 3}log pseudolikelihood = {res:-30.457381}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     44.00
{txt}Log pseudolikelihood =   {res}-30.457381                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 83:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}               _t{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_Rate_wotw {c |}{col 19}{res}{space 2} .0389603{col 31}{space 2} .0177932{col 42}{space 1}    2.19{col 51}{space 3}0.029{col 59}{space 4} .0040863{col 72}{space 3} .0738343
{txt}{space 4}unpkf_imprate {c |}{col 19}{res}{space 2}-.0002879{col 31}{space 2} .0104319{col 42}{space 1}   -0.03{col 51}{space 3}0.978{col 59}{space 4} -.020734{col 72}{space 3} .0201581
{txt}{space 8}dead_1000 {c |}{col 19}{res}{space 2} .0003461{col 31}{space 2} .0008768{col 42}{space 1}    0.39{col 51}{space 3}0.693{col 59}{space 4}-.0013724{col 72}{space 3} .0020646
{txt}{space 3}war_dur_months {c |}{col 19}{res}{space 2}-.0005322{col 31}{space 2} .0046701{col 42}{space 1}   -0.11{col 51}{space 3}0.909{col 59}{space 4}-.0096854{col 72}{space 3}  .008621
{txt}{space 6}infant_rate {c |}{col 19}{res}{space 2}-.0189041{col 31}{space 2} .0131729{col 42}{space 1}   -1.44{col 51}{space 3}0.151{col 59}{space 4}-.0447224{col 72}{space 3} .0069142
{txt}{space 4}conflict_type {c |}{col 19}{res}{space 2}-.6083803{col 31}{space 2} 1.000645{col 42}{space 1}   -0.61{col 51}{space 3}0.543{col 59}{space 4}-2.569608{col 72}{space 3} 1.352847
{txt}{space 2}polity_2_1lag_1 {c |}{col 19}{res}{space 2} .0210175{col 31}{space 2} .0855686{col 42}{space 1}    0.25{col 51}{space 3}0.806{col 59}{space 4}-.1466938{col 72}{space 3} .1887288
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} 3.263078{col 31}{space 2} 2.283236{col 42}{space 1}    1.43{col 51}{space 3}0.153{col 59}{space 4}-1.211981{col 72}{space 3} 7.738137
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
            /ln_p {c |}{col 19}{res}{space 2}-.0393075{col 31}{space 2} .1881246{col 42}{space 1}   -0.21{col 51}{space 3}0.834{col 59}{space 4} -.408025{col 72}{space 3}   .32941
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                p{col 19}{c |}{res}{space 2}  .961455{col 31}{space 2} .1808734{col 59}{space 4} .6649623{col 72}{space 3} 1.390148
{col 1}{txt}              1/p{col 19}{c |}{res}{space 2}  1.04009{col 31}{space 2} .1956666{col 59}{space 4}  .719348{col 72}{space 3} 1.503845
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //online appendix weighted index based on how frequent the SSR provision was in accord
. //Provision                                     freq.           freq/Total
. //ceasefire                                     29                      0.153
. //demobalization                                25                      0.132
. //disarmamnet                                   28                      0.148
. //military reform                               26                      0.138
. //paramilitary                                  16                      0.085
. //police reform                                 24                      0.127
. //reintegration                                 27                      0.143
. //withdrawal                                    14                      0.074
. //_______________________________________________________________________________
. //Total                                         189                     1.000
. 
. //SSR Index based on frequency weight and includes all 8 SSR provisions 
. gen SSR_Imp_weight = ((cease_imp*0.153) + (demob_imp*0.132) + (disarm_imp*0.148)  + (milrfm_imp*0.138)  + (pargrp_imp*0.085)  + (polrfm_imp*0.127) + (reint_imp*0.143)  + (with_imp*0.074))
{txt}
{com}. gen SSR_IMP_expweight = (3*0.153)+(3*0.132) + (3*0.148) + (3*0.138) + (3*0.085) + (3*0.127) + (3*0.143) + (3*0.074)
{txt}
{com}. gen SSR_IMP_weightedRate = (SSR_Imp_weight/SSR_IMP_expweight)*100
{txt}
{com}. 
. 
. //Replicates Model 3 in current version
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure( sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_weightedRate unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.288721}  
Iteration 2:{space 3}log pseudolikelihood = {res:-20.814164}  
Iteration 3:{space 3}log pseudolikelihood = {res:-19.954015}  
Iteration 4:{space 3}log pseudolikelihood = {res: -19.92027}  
Iteration 5:{space 3}log pseudolikelihood = {res:-19.920195}  
Iteration 6:{space 3}log pseudolikelihood = {res:-19.920195}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}    102.10
{txt}Log pseudolikelihood =   {res}-19.920195                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 86:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                  _t{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_weightedRate {c |}{col 22}{res}{space 2} .0311068{col 34}{space 2} .0071461{col 45}{space 1}    4.35{col 54}{space 3}0.000{col 62}{space 4} .0171007{col 75}{space 3} .0451129
{txt}{space 7}unpkf_imprate {c |}{col 22}{res}{space 2}  .005422{col 34}{space 2} .0051557{col 45}{space 1}    1.05{col 54}{space 3}0.293{col 62}{space 4} -.004683{col 75}{space 3}  .015527
{txt}{space 11}dead_1000 {c |}{col 22}{res}{space 2}-.0004002{col 34}{space 2} .0004443{col 45}{space 1}   -0.90{col 54}{space 3}0.368{col 62}{space 4}-.0012711{col 75}{space 3} .0004706
{txt}{space 6}war_dur_months {c |}{col 22}{res}{space 2}-.0016738{col 34}{space 2} .0035562{col 45}{space 1}   -0.47{col 54}{space 3}0.638{col 62}{space 4}-.0086438{col 75}{space 3} .0052963
{txt}{space 9}infant_rate {c |}{col 22}{res}{space 2}-.0176951{col 34}{space 2} .0052318{col 45}{space 1}   -3.38{col 54}{space 3}0.001{col 62}{space 4}-.0279492{col 75}{space 3} -.007441
{txt}{space 7}conflict_type {c |}{col 22}{res}{space 2} .7174344{col 34}{space 2} .7221566{col 45}{space 1}    0.99{col 54}{space 3}0.320{col 62}{space 4}-.6979664{col 75}{space 3} 2.132835
{txt}{space 5}polity_2_1lag_1 {c |}{col 22}{res}{space 2} .0839006{col 34}{space 2} .0460741{col 45}{space 1}    1.82{col 54}{space 3}0.069{col 62}{space 4}-.0064031{col 75}{space 3} .1742042
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} 2.225114{col 34}{space 2}  .973403{col 45}{space 1}    2.29{col 54}{space 3}0.022{col 62}{space 4} .3172793{col 75}{space 3} 4.132949
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
               /ln_p {c |}{col 22}{res}{space 2} .6427779{col 34}{space 2} .2557419{col 45}{space 1}    2.51{col 54}{space 3}0.012{col 62}{space 4} .1415331{col 75}{space 3} 1.144023
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   p{col 22}{c |}{res}{space 2} 1.901756{col 34}{space 2} .4863587{col 62}{space 4} 1.152039{col 75}{space 3} 3.139372
{col 1}{txt}                 1/p{col 22}{c |}{res}{space 2} .5258297{col 34}{space 2} .1344767{col 62}{space 4} .3185351{col 75}{space 3} .8680265
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //Replicates Model 6 (non-signatories) in RR1 version
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(nonsig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}nonsig_minor_war != 0 & nonsig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       79{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      227{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       11{txt}  failures in single failure-per-subject data
{res}      227{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_weightedRate  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-35.370724}  
Iteration 2:{space 3}log pseudolikelihood = {res:-29.606396}  
Iteration 3:{space 3}log pseudolikelihood = {res:-29.506262}  
Iteration 4:{space 3}log pseudolikelihood = {res:-29.505986}  
Iteration 5:{space 3}log pseudolikelihood = {res:-29.505986}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     47.40
{txt}Log pseudolikelihood =   {res}-29.505986                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 86:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                  _t{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
SSR_IMP_weightedRate {c |}{col 22}{res}{space 2} .0488063{col 34}{space 2} .0194162{col 45}{space 1}    2.51{col 54}{space 3}0.012{col 62}{space 4} .0107513{col 75}{space 3} .0868613
{txt}{space 7}unpkf_imprate {c |}{col 22}{res}{space 2} .0003339{col 34}{space 2} .0095525{col 45}{space 1}    0.03{col 54}{space 3}0.972{col 62}{space 4}-.0183886{col 75}{space 3} .0190564
{txt}{space 11}dead_1000 {c |}{col 22}{res}{space 2} .0002059{col 34}{space 2} .0008418{col 45}{space 1}    0.24{col 54}{space 3}0.807{col 62}{space 4}-.0014439{col 75}{space 3} .0018558
{txt}{space 6}war_dur_months {c |}{col 22}{res}{space 2} -.000199{col 34}{space 2} .0045501{col 45}{space 1}   -0.04{col 54}{space 3}0.965{col 62}{space 4}-.0091171{col 75}{space 3} .0087191
{txt}{space 9}infant_rate {c |}{col 22}{res}{space 2}-.0163131{col 34}{space 2} .0120409{col 45}{space 1}   -1.35{col 54}{space 3}0.175{col 62}{space 4}-.0399129{col 75}{space 3} .0072867
{txt}{space 7}conflict_type {c |}{col 22}{res}{space 2}-.4577471{col 34}{space 2} .9522648{col 45}{space 1}   -0.48{col 54}{space 3}0.631{col 62}{space 4}-2.324152{col 75}{space 3} 1.408658
{txt}{space 5}polity_2_1lag_1 {c |}{col 22}{res}{space 2} .0267931{col 34}{space 2} .0797975{col 45}{space 1}    0.34{col 54}{space 3}0.737{col 62}{space 4}-.1296072{col 75}{space 3} .1831935
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} 2.498693{col 34}{space 2}  2.20169{col 45}{space 1}    1.13{col 54}{space 3}0.256{col 62}{space 4} -1.81654{col 75}{space 3} 6.813926
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
               /ln_p {c |}{col 22}{res}{space 2} .0226534{col 34}{space 2} .1994516{col 45}{space 1}    0.11{col 54}{space 3}0.910{col 62}{space 4}-.3682645{col 75}{space 3} .4135713
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   p{col 22}{c |}{res}{space 2} 1.022912{col 34}{space 2} .2040214{col 62}{space 4} .6919341{col 75}{space 3} 1.512209
{col 1}{txt}                 1/p{col 22}{c |}{res}{space 2} .9776013{col 34}{space 2} .1949841{col 62}{space 4} .6612844{col 75}{space 3} 1.445224
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //SSR Index based on given weights that weight some provision more than others.
. 
. //Giving weight 
. //Provision                                                     weight
. //ceasefire                                                     0.2
. //demobalization                                                0.2
. //disarmamnet                                                   0.2
. //military reform                                               0.15
. //paramilitary                                                  0.025
. //police reform                                                 0.05
. //reintegration                                                 0.15
. //withdrawal                                                    0.025
. //__________________________________________________________________________                                                    
. //Total                                                         1.00
. 
. gen SSR_IMP_GW = ((cease_imp*0.2) + (demob_imp*0.2) + (disarm_imp*0.2)  + (milrfm_imp*0.15)  + (pargrp_imp*0.025)  + (polrfm_imp*0.05) + (reint_imp*0.15)  + (with_imp*0.025))
{txt}
{com}. gen SSR_IMP_GWEXP = (3*0.2)+(3*0.2) + (3*0.2) + (3*0.15) + (3*0.025) + (3*0.05) + (3*0.15) + (3*0.025)
{txt}
{com}. gen SSR_IMP_GWRate = (SSR_IMP_GW/SSR_IMP_GWEXP)*100
{txt}
{com}. 
. //Replicates Model 3 in current version
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure( sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_GWRate unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25.561832}  
Iteration 2:{space 3}log pseudolikelihood = {res:-21.450333}  
Iteration 3:{space 3}log pseudolikelihood = {res:-20.765899}  
Iteration 4:{space 3}log pseudolikelihood = {res:-20.747025}  
Iteration 5:{space 3}log pseudolikelihood = {res:-20.746999}  
Iteration 6:{space 3}log pseudolikelihood = {res:-20.746999}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}     85.02
{txt}Log pseudolikelihood =   {res}-20.746999                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}SSR_IMP_GWRate {c |}{col 17}{res}{space 2} .0295078{col 29}{space 2} .0073256{col 40}{space 1}    4.03{col 49}{space 3}0.000{col 57}{space 4} .0151499{col 70}{space 3} .0438657
{txt}{space 2}unpkf_imprate {c |}{col 17}{res}{space 2}  .006827{col 29}{space 2} .0056368{col 40}{space 1}    1.21{col 49}{space 3}0.226{col 57}{space 4} -.004221{col 70}{space 3} .0178749
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2}-.0002634{col 29}{space 2} .0005036{col 40}{space 1}   -0.52{col 49}{space 3}0.601{col 57}{space 4}-.0012505{col 70}{space 3} .0007238
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0025152{col 29}{space 2} .0037467{col 40}{space 1}   -0.67{col 49}{space 3}0.502{col 57}{space 4}-.0098586{col 70}{space 3} .0048282
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0197578{col 29}{space 2} .0059725{col 40}{space 1}   -3.31{col 49}{space 3}0.001{col 57}{space 4}-.0314638{col 70}{space 3}-.0080519
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2} .6116788{col 29}{space 2} .7497915{col 40}{space 1}    0.82{col 49}{space 3}0.415{col 57}{space 4}-.8578855{col 70}{space 3} 2.081243
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .0808473{col 29}{space 2} .0479349{col 40}{space 1}    1.69{col 49}{space 3}0.092{col 57}{space 4}-.0131033{col 70}{space 3}  .174798
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  2.52318{col 29}{space 2} 1.065083{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .4356549{col 70}{space 3} 4.610705
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .5666057{col 29}{space 2} .2455863{col 40}{space 1}    2.31{col 49}{space 3}0.021{col 57}{space 4} .0852653{col 70}{space 3} 1.047946
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.762275{col 29}{space 2} .4327907{col 57}{space 4} 1.089006{col 70}{space 3} 2.851788
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2} .5674483{col 29}{space 2} .1393575{col 57}{space 4} .3506573{col 70}{space 3} .9182686
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //Replicates Model 6 (non-signatories) in RR1 version
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure(nonsig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}nonsig_minor_war != 0 & nonsig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       79{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      227{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       11{txt}  failures in single failure-per-subject data
{res}      227{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. streg SSR_IMP_GWRate  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}nonsig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-38.929243
{txt}Iteration 1:   log pseudolikelihood = {res}-37.749712
{txt}Iteration 2:   log pseudolikelihood = {res}-37.709275
{txt}Iteration 3:   log pseudolikelihood = {res}-37.709227
{txt}Iteration 4:   log pseudolikelihood = {res}-37.709227

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37.709227}  
Iteration 1:{space 3}log pseudolikelihood = {res:-36.592306}  
Iteration 2:{space 3}log pseudolikelihood = {res:-29.934919}  
Iteration 3:{space 3}log pseudolikelihood = {res:-29.790414}  
Iteration 4:{space 3}log pseudolikelihood = {res:-29.788653}  
Iteration 5:{space 3}log pseudolikelihood = {res:-29.788653}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       211
{txt}No. of failures      = {res}          11
{txt}Time at risk         = {res}         211
                                                   {txt}Wald chi2({res}7{txt})    ={res}     45.50
{txt}Log pseudolikelihood =   {res}-29.788653                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}SSR_IMP_GWRate {c |}{col 17}{res}{space 2} .0416361{col 29}{space 2} .0174345{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4} .0074651{col 70}{space 3} .0758071
{txt}{space 2}unpkf_imprate {c |}{col 17}{res}{space 2} .0021248{col 29}{space 2} .0105979{col 40}{space 1}    0.20{col 49}{space 3}0.841{col 57}{space 4}-.0186467{col 70}{space 3} .0228963
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2}  .000241{col 29}{space 2} .0008669{col 40}{space 1}    0.28{col 49}{space 3}0.781{col 57}{space 4}-.0014581{col 70}{space 3} .0019401
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0004706{col 29}{space 2} .0045545{col 40}{space 1}   -0.10{col 49}{space 3}0.918{col 57}{space 4}-.0093974{col 70}{space 3} .0084561
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0181668{col 29}{space 2} .0119271{col 40}{space 1}   -1.52{col 49}{space 3}0.128{col 57}{space 4}-.0415434{col 70}{space 3} .0052099
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2}-.5638312{col 29}{space 2} .9734864{col 40}{space 1}   -0.58{col 49}{space 3}0.562{col 57}{space 4}-2.471829{col 70}{space 3} 1.344167
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2}  .027972{col 29}{space 2} .0816192{col 40}{space 1}    0.34{col 49}{space 3}0.732{col 57}{space 4}-.1319987{col 70}{space 3} .1879428
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.788264{col 29}{space 2} 2.185097{col 40}{space 1}    1.28{col 49}{space 3}0.202{col 57}{space 4}-1.494447{col 70}{space 3} 7.070975
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .0071038{col 29}{space 2} .1945831{col 40}{space 1}    0.04{col 49}{space 3}0.971{col 57}{space 4}-.3742721{col 70}{space 3} .3884796
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.007129{col 29}{space 2} .1959703{col 57}{space 4} .6877897{col 70}{space 3} 1.474737
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2} .9929214{col 29}{space 2} .1932057{col 57}{space 4}  .678087{col 70}{space 3} 1.453933
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. sum SSR_IMP_Rate_wotw SSR_IMP_weightedRate SSR_IMP_GWRate 

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
SSR_IMP_Ra~w {c |}{res}       340    44.45378    28.61561          0    95.2381
{txt}SSR_IMP_we~e {c |}{res}       340    44.43471    26.72278          0       90.3
{txt}SSR_IMP_GW~e {c |}{res}       340    47.66422    28.94185          0   96.66667
{txt}
{com}. // SSR_IMP_Rate_wotw - index without withdrawal of troops
. // SSR_IMP_weightedRate - weighted index based on provision's frequency see abote table
. //SSR_IMP_GWRate - randomely assigned index see above table
. 
. //Factor Analysis
. factor  cease_imp demob_imp disarm_imp  milrfm_imp  pargrp_imp  polrfm_imp reint_imp  with_imp if  exclude_cases==0, pcf
{txt}(obs=314)

Factor analysis/correlation{col 52}Number of obs    = {res}     314
{col 5}{txt}Method: principal-component factors{col 52}Retained factors = {res}       3
{col 5}{txt}Rotation: (unrotated){col 52}Number of params = {res}      21

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      3.13513      1.85103            0.3919       0.3919
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      1.28410      0.27541            0.1605       0.5524
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      1.00869      0.30385            0.1261       0.6785
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}      0.70484      0.13212            0.0881       0.7666
{txt}{col 5}{ralign 11:Factor5}  {c |}{res}      0.57271      0.02892            0.0716       0.8382
{txt}{col 5}{ralign 11:Factor6}  {c |}{res}      0.54380      0.05296            0.0680       0.9062
{txt}{col 5}{ralign 11:Factor7}  {c |}{res}      0.49084      0.23094            0.0614       0.9675
{txt}{col 5}{ralign 11:Factor8}  {c |}{res}      0.25990            .            0.0325       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}28{txt}) ={res}  675.04{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:cease_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6028}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1690}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.5106}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3473}}}{space 1}
{space 4}{space 0}{ralign 12:demob_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8026}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2268}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2185}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2566}}}{space 1}
{space 4}{space 0}{ralign 12:disarm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5837}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1700}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.6298}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2338}}}{space 1}
{space 4}{space 0}{ralign 12:milrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7051}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0951}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.4105}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3253}}}{space 1}
{space 4}{space 0}{ralign 12:pargrp_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6003}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4310}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0603}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4502}}}{space 1}
{space 4}{space 0}{ralign 12:polrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6673}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4221}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1852}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3422}}}{space 1}
{space 4}{space 0}{ralign 12:reint_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6740}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.4353}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0300}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3553}}}{space 1}
{space 4}{space 0}{ralign 12:with_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.1721}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.7828}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3102}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2614}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. rotate

{txt}Factor analysis/correlation{col 52}Number of obs    = {res}     314
{col 5}{txt}Method: principal-component factors{col 52}Retained factors = {res}       3
{col 5}{txt}Rotation: orthogonal varimax (Kaiser off){col 52}Number of params = {res}      21

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Variance}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      2.11756      0.06101            0.2647       0.2647
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      2.05655      0.80275            0.2571       0.5218
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      1.25380            .            0.1567       0.6785
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}28{txt}) ={res}  675.04{txt} Prob>chi2 ={res} 0.0000

{txt}Rotated factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:cease_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8010}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0346}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0993}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3473}}}{space 1}
{space 4}{space 0}{ralign 12:demob_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.3608}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.7602}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1881}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2566}}}{space 1}
{space 4}{space 0}{ralign 12:disarm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0301}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.8736}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0457}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2338}}}{space 1}
{space 4}{space 0}{ralign 12:milrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7873}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1909}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1357}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3253}}}{space 1}
{space 4}{space 0}{ralign 12:pargrp_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6087}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2780}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3193}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4502}}}{space 1}
{space 4}{space 0}{ralign 12:polrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5019}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4935}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4030}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3422}}}{space 1}
{space 4}{space 0}{ralign 12:reint_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.3159}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.5906}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.4427}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3553}}}{space 1}
{space 4}{space 0}{ralign 12:with_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0525}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0901}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.8531}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2614}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{c  BT}{hline 14}

Factor rotation matrix

{space 4}{hline 13}{c  TT}{hline 9}{hline 9}{hline 9}
{space 4}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 7:Factor1}{space 1}{space 1}{ralign 7:Factor2}{space 1}{space 1}{ralign 7:Factor3}{space 1}
{space 4}{hline 13}{c   +}{hline 9}{hline 9}{hline 9}
{space 4}{space 0}{ralign 12:Factor1}{space 1}{c |}{space 1}{ralign 7:{res:{sf: 0.7120}}}{space 1}{space 1}{ralign 7:{res:{sf: 0.6970}}}{space 1}{space 1}{ralign 7:{res:{sf:-0.0844}}}{space 1}
{space 4}{space 0}{ralign 12:Factor2}{space 1}{c |}{space 1}{ralign 7:{res:{sf: 0.3342}}}{space 1}{space 1}{ralign 7:{res:{sf:-0.2308}}}{space 1}{space 1}{ralign 7:{res:{sf: 0.9138}}}{space 1}
{space 4}{space 0}{ralign 12:Factor3}{space 1}{c |}{space 1}{ralign 7:{res:{sf:-0.6175}}}{space 1}{space 1}{ralign 7:{res:{sf: 0.6789}}}{space 1}{space 1}{ralign 7:{res:{sf: 0.3973}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 9}{hline 9}{hline 9}

{com}. predict factor1 factor2 factor3 factor4 factor5
{txt}(regression scoring assumed)
(excess variables dropped)

{p 0 0 2}Scoring coefficients (method = regression; based on varimax rotated factors){p_end}

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:cease_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.49349}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.24000}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.09705}}}{space 1}
{space 4}{space 0}{ralign 12:demob_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:-0.01052}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.36630}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.09691}}}{space 1}
{space 4}{space 0}{ralign 12:disarm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:-0.29723}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.58420}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.11143}}}{space 1}
{space 4}{space 0}{ralign 12:milrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.43617}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.13658}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.11302}}}{space 1}
{space 4}{space 0}{ralign 12:pargrp_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.28541}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.01544}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.26685}}}{space 1}
{space 4}{space 0}{ralign 12:polrfm_imp~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.14808}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.19713}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.35535}}}{space 1}
{space 4}{space 0}{ralign 12:reint_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.02143}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.24827}}}{space 1}{space 1}{ralign 8:{res:{sf:-0.31609}}}{space 1}
{space 4}{space 0}{ralign 12:with_implem}{space 1}{c |}{space 1}{ralign 8:{res:{sf:-0.02524}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.02980}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.68385}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}


{com}. 
.    // --------------------------------------------
.    //    Variable |  Factor1   Factor2   Factor3 
.    //-------------+------------------------------
.    // cease_implem |  0.49349  -0.24000  -0.09705 
.    // demob_implem | -0.01052   0.36630  -0.09691 
.    // disarm_imp~m | -0.29723   0.58420   0.11143 
.    // milrfm_imp~m |  0.43617  -0.13658  -0.11302 
.    //pargrp_imp~m |  0.28541   0.01544   0.26685 
.    // polrfm_imp~m |  0.14808   0.19713   0.35535 
.    // reint_implem |  0.02143   0.24827  -0.31609 
.    //  with_implem | -0.02524   0.02980   0.68385 
.    // --------------------------------------------
. 
. //Replicates Model 3 - Dimensions of SSR based on Factor Analysis
. //Factor 1  
. drop  _st _d _t _t0
{txt}
{com}. stset year_count, id(caseid) failure( sig_minor_war) origin(time year_count)

                {txt}id:  {res}caseid
     {txt}failure event:  {res}sig_minor_war != 0 & sig_minor_war < .
{txt}obs. time interval:  {res}(year_count[_n-1], year_count]
{txt} exit on or before:  {res}failure
    {txt}t for analysis:  {res}(time-origin)
            {txt}origin:  {res}time year_count

{txt}{hline 78}
{res}      340{txt}  total obs.
{res}       34{txt}  obs. end on or before enter()
{res}       70{txt}  obs. begin on or after (first) failure
{hline 78}
{res}      236{txt}  obs. remaining, representing
{res}       34{txt}  subjects
{res}       10{txt}  failures in single failure-per-subject data
{res}      236{txt}  total analysis time at risk, at risk from t = {res}        0
                             {txt}earliest observed entry t = {res}        0
                                  {txt}last observed exit t = {res}        9
{txt}
{com}. gen SSR_Imp_F1 = (cease_imp + milrfm_imp  + pargrp_imp  + polrfm_imp)
{txt}
{com}. gen SSR_IMP_RateF1 = (SSR_Imp_F1/12)*100
{txt}
{com}. streg  SSR_IMP_RateF1  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31.060354}  
Iteration 2:{space 3}log pseudolikelihood = {res:-25.171545}  
Iteration 3:{space 3}log pseudolikelihood = {res:-22.589967}  
Iteration 4:{space 3}log pseudolikelihood = {res:-22.509851}  
Iteration 5:{space 3}log pseudolikelihood = {res:-22.509406}  
Iteration 6:{space 3}log pseudolikelihood = {res:-22.509406}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}     67.95
{txt}Log pseudolikelihood =   {res}-22.509406                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}SSR_IMP_RateF1 {c |}{col 17}{res}{space 2} .0233927{col 29}{space 2} .0064958{col 40}{space 1}    3.60{col 49}{space 3}0.000{col 57}{space 4} .0106612{col 70}{space 3} .0361242
{txt}{space 2}unpkf_imprate {c |}{col 17}{res}{space 2} .0082844{col 29}{space 2} .0052781{col 40}{space 1}    1.57{col 49}{space 3}0.117{col 57}{space 4}-.0020605{col 70}{space 3} .0186292
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2}-.0006164{col 29}{space 2} .0005564{col 40}{space 1}   -1.11{col 49}{space 3}0.268{col 57}{space 4} -.001707{col 70}{space 3} .0004742
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0001086{col 29}{space 2}  .004405{col 40}{space 1}   -0.02{col 49}{space 3}0.980{col 57}{space 4}-.0087422{col 70}{space 3}  .008525
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0175411{col 29}{space 2} .0065069{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4}-.0302943{col 70}{space 3}-.0047879
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2} 1.052694{col 29}{space 2} .8518871{col 40}{space 1}    1.24{col 49}{space 3}0.217{col 57}{space 4}-.6169737{col 70}{space 3} 2.722363
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .1243086{col 29}{space 2} .0504472{col 40}{space 1}    2.46{col 49}{space 3}0.014{col 57}{space 4}  .025434{col 70}{space 3} .2231833
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.272279{col 29}{space 2} 1.341408{col 40}{space 1}    1.69{col 49}{space 3}0.090{col 57}{space 4}-.3568318{col 70}{space 3}  4.90139
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .4783794{col 29}{space 2} .2800047{col 40}{space 1}    1.71{col 49}{space 3}0.088{col 57}{space 4}-.0704198{col 70}{space 3} 1.027179
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.613457{col 29}{space 2} .4517757{col 57}{space 4} .9320025{col 70}{space 3} 2.793174
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2}  .619787{col 29}{space 2} .1735433{col 57}{space 4} .3580157{col 70}{space 3} 1.072958
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //Factor2
. gen SSR_Imp_F2 = (demob_imp + disarm_imp + polrfm_imp + reint_imp )
{txt}
{com}. gen SSR_IMP_RateF2 = (SSR_Imp_F2/24)*100
{txt}
{com}. streg  SSR_IMP_RateF2  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-33.533293}  
Iteration 2:{space 3}log pseudolikelihood = {res:-26.366384}  
Iteration 3:{space 3}log pseudolikelihood = {res: -20.38153}  
Iteration 4:{space 3}log pseudolikelihood = {res:-20.205619}  
Iteration 5:{space 3}log pseudolikelihood = {res: -20.20536}  
Iteration 6:{space 3}log pseudolikelihood = {res: -20.20536}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}     98.38
{txt}Log pseudolikelihood =   {res} -20.20536                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}SSR_IMP_RateF2 {c |}{col 17}{res}{space 2} .0562758{col 29}{space 2} .0157949{col 40}{space 1}    3.56{col 49}{space 3}0.000{col 57}{space 4} .0253183{col 70}{space 3} .0872333
{txt}{space 2}unpkf_imprate {c |}{col 17}{res}{space 2} .0050846{col 29}{space 2} .0061312{col 40}{space 1}    0.83{col 49}{space 3}0.407{col 57}{space 4}-.0069322{col 70}{space 3} .0171015
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2}-.0000979{col 29}{space 2}  .000486{col 40}{space 1}   -0.20{col 49}{space 3}0.840{col 57}{space 4}-.0010504{col 70}{space 3} .0008546
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0037395{col 29}{space 2} .0035138{col 40}{space 1}   -1.06{col 49}{space 3}0.287{col 57}{space 4}-.0106263{col 70}{space 3} .0031474
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0212556{col 29}{space 2} .0055689{col 40}{space 1}   -3.82{col 49}{space 3}0.000{col 57}{space 4}-.0321705{col 70}{space 3}-.0103407
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2} .7150258{col 29}{space 2} .7577015{col 40}{space 1}    0.94{col 49}{space 3}0.345{col 57}{space 4}-.7700419{col 70}{space 3} 2.200093
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .0615711{col 29}{space 2} .0542451{col 40}{space 1}    1.14{col 49}{space 3}0.256{col 57}{space 4}-.0447472{col 70}{space 3} .1678895
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  3.08401{col 29}{space 2} 1.010262{col 40}{space 1}    3.05{col 49}{space 3}0.002{col 57}{space 4} 1.103932{col 70}{space 3} 5.064087
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .5971992{col 29}{space 2} .2801214{col 40}{space 1}    2.13{col 49}{space 3}0.033{col 57}{space 4} .0481713{col 70}{space 3} 1.146227
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.817022{col 29}{space 2} .5089869{col 57}{space 4}  1.04935{col 70}{space 3}   3.1463
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2} .5503509{col 29}{space 2} .1541651{col 57}{space 4} .3178337{col 70}{space 3} .9529706
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. //Factor3
. 
. gen SSR_Imp_F3 = (disarm_imp  + pargrp_imp  + polrfm_imp + with_imp)
{txt}
{com}. gen SSR_IMP_RateF3 = (SSR_Imp_F3/24)*100
{txt}
{com}. streg  SSR_IMP_RateF3  unpkf_imprate  dead_1000   war_dur  infant_rate conflict_type  polity_2_1lag_1 if  exclude_cases==0, cluster (cowcode) d(w) time

         {txt}failure _d:  {res}sig_minor_war
   {txt}analysis time _t:  {res}(year_count-origin)
             {txt}origin:  {res}time year_count
                 {txt}id:  {res}caseid

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-36.770522
{txt}Iteration 1:   log pseudolikelihood = {res}-35.596471
{txt}Iteration 2:   log pseudolikelihood = {res}-35.547671
{txt}Iteration 3:   log pseudolikelihood = {res}-35.547589
{txt}Iteration 4:   log pseudolikelihood = {res}-35.547589

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-35.547589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-30.308112}  
Iteration 2:{space 3}log pseudolikelihood = {res:-22.775172}  
Iteration 3:{space 3}log pseudolikelihood = {res:-20.210876}  
Iteration 4:{space 3}log pseudolikelihood = {res:-20.080505}  
Iteration 5:{space 3}log pseudolikelihood = {res:-20.080366}  
Iteration 6:{space 3}log pseudolikelihood = {res:-20.080366}  
{res}
{txt}Weibull regression -- accelerated failure-time form 

No. of subjects      = {res}          34                {txt}Number of obs   ={res}       219
{txt}No. of failures      = {res}          10
{txt}Time at risk         = {res}         219
                                                   {txt}Wald chi2({res}7{txt})    ={res}    101.09
{txt}Log pseudolikelihood =   {res}-20.080366                {txt}Prob > chi2     ={res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:30} clusters in cowcode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}SSR_IMP_RateF3 {c |}{col 17}{res}{space 2} .0632354{col 29}{space 2} .0135215{col 40}{space 1}    4.68{col 49}{space 3}0.000{col 57}{space 4} .0367337{col 70}{space 3}  .089737
{txt}{space 2}unpkf_imprate {c |}{col 17}{res}{space 2} .0067278{col 29}{space 2} .0049556{col 40}{space 1}    1.36{col 49}{space 3}0.175{col 57}{space 4}-.0029851{col 70}{space 3} .0164407
{txt}{space 6}dead_1000 {c |}{col 17}{res}{space 2}-.0008613{col 29}{space 2} .0003844{col 40}{space 1}   -2.24{col 49}{space 3}0.025{col 57}{space 4}-.0016148{col 70}{space 3}-.0001078
{txt}{space 1}war_dur_months {c |}{col 17}{res}{space 2}-.0001941{col 29}{space 2} .0027356{col 40}{space 1}   -0.07{col 49}{space 3}0.943{col 57}{space 4}-.0055558{col 70}{space 3} .0051677
{txt}{space 4}infant_rate {c |}{col 17}{res}{space 2}-.0152515{col 29}{space 2} .0045907{col 40}{space 1}   -3.32{col 49}{space 3}0.001{col 57}{space 4}-.0242492{col 70}{space 3}-.0062538
{txt}{space 2}conflict_type {c |}{col 17}{res}{space 2}  1.53032{col 29}{space 2} .7747825{col 40}{space 1}    1.98{col 49}{space 3}0.048{col 57}{space 4} .0117742{col 70}{space 3} 3.048866
{txt}polity_2_1lag_1 {c |}{col 17}{res}{space 2} .1091808{col 29}{space 2} .0478541{col 40}{space 1}    2.28{col 49}{space 3}0.023{col 57}{space 4} .0153886{col 70}{space 3}  .202973
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.997096{col 29}{space 2} .8508529{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .3294544{col 70}{space 3} 3.664737
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /ln_p {c |}{col 17}{res}{space 2} .6172717{col 29}{space 2} .2513843{col 40}{space 1}    2.46{col 49}{space 3}0.014{col 57}{space 4} .1245676{col 70}{space 3} 1.109976
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              p{col 17}{c |}{res}{space 2} 1.853863{col 29}{space 2}  .466032{col 57}{space 4} 1.132659{col 70}{space 3} 3.034285
{col 1}{txt}            1/p{col 17}{c |}{res}{space 2} .5394141{col 29}{space 2} .1356002{col 57}{space 4} .3295669{col 70}{space 3} .8828786
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2.DSS-OKIU3QJMAS9\Desktop\JPR RR2\RR3\Replication Files\JPR-PAM-ID-JOSHI, QUINN & REGAN.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 8 Oct 2014, 10:24:05
{txt}{.-}
{smcl}
{txt}{sf}{ul off}